Tactical fleet mix computation using multiobjective evolutionary optimization

Author

Stuive, Leanne ; Wesolkowski, Slawo ; Ghanmi, Ahmed

Author_Institution

Canadian Forces Aerosp. Warfare Centre OR Team, Ottawa, ON, Canada

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

7

Abstract

A multi-objective model for determining optimal fleet mixes for a set of non-concurrent tactical missions is studied. An implementation of the multiobjective evolutionary algorithm (MEA) NSGA-II is used to solve the problem, and it is compared to an exhaustive search of the fleet mix space as well as a solution set obtained by a Mixed Integer Non-Linear Program. The exhaustive and MEA searches are compared with respect to both accuracy and computational complexity. The use of an alternative genotypic representation is investigated; its slow convergence is used to demonstrate the importance of chromosome choice, aligning with past research on locality and redundancy in genotypic representations.

Keywords

computational complexity; evolutionary computation; integer programming; military vehicles; nonlinear programming; NSGA-II; computational complexity; exhaustive search; fleet mix space; genotypic representation; mixed integer nonlinear program; multiobjective evolutionary optimization; multiobjective model; nonconcurrent tactical missions; tactical fleet mix computation; Evolutionary computation; Indexes; Optimization; Procurement; Search problems; Upper bound; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2010 IEEE Congress on

Conference_Location

Barcelona

Print_ISBN

978-1-4244-6909-3

Type

conf

DOI

10.1109/CEC.2010.5586285

Filename

5586285